Web Scraper Shortcode WordPress Plugin Review

This short post is on the WP-plugin called Web Scraper Shortcode, that enables one to retrieve a portion of a web page or a whole page and insert it directly into a post. This plugin might be used for getting fresh data or images from web pages for your WordPress driven page without even visiting it. More scraping plugins and sowtware you can find in here.

To install it in WordPress go to Plugins -> Add New.
Usage

The plugin scrapes the page content and applies parameters to this scraped page if specified. To use the plugin just insert the

[web-scraper ]

shortcode into the HTML view of the WordPress page where you want to display the excerpts of a page or the whole page. The parameters are as follows:

    url (self explanatory)
    element – the dom navigation element notation, similar to XPath.
    limit – the maximum number of elements to be scraped and inserted if the element notation points to several of them (like elements of the same class).

The use of the plugin is of the dom (Data Object Model) notation, where consecutive dom nodes are stated like node1.node2; for example: element = ‘div.img’. The specific element scrape goes thru ‘#notation’. Example: if you want to scrape several ‘div’ elements of the class ‘red’ (<div class=’red’>…<div>), you need to specify the element attribute this way: element = ‘div#red’.
How to find DOM notation?

But for inexperienced users, how is it possible to find the dom notation of the desired element(s) from the web page? Web Developer Tools are a handy means for this. I would refer you to this paragraph on how to invoke Web Developer Tools in the browser (Google Chrome) and select a single page element to inspect it. As you select it with the ‘loupe’ tool, on the bottom line you’ll see the blue box with the element’s dom notation:


The plugin content

As one who works with web scraping, I was curious about  the means that the plugin uses for scraping. As I looked at the plugin code, it turned out that the plugin acquires a web page through ‘simple_html_dom‘ class:

    require_once(‘simple_html_dom.php’);
    $html = file_get_html($url);
    then the code performs iterations over the designated elements with the set limit

Pitfalls

    Be careful if you put two or more [web-scraper] shortcodes on your website, since downloading other pages will drastically slow the page load speed. Even if you want only a small element, the PHP engine first loads the whole page and then iterates over its elements.
    You need to remember that many pictures on the web are indicated by shortened URLs. So when such an image gets extracted it might be visible to you in this way: , since the URL is shortened and the plugin does not take note of  its base URL.
    The error “Fatal error: Call to a member function find() on a non-object …” will occur if you put this shortcode in a text-overloaded post.

Summary

I’d recommend using this plugin for short posts to be added with other posts’ elements. The use of this plugin is limited though.



Source: http://extract-web-data.com/web-scraper-shortcode-wordpress-plugin-review/

Visual Web Ripper: Using External Input Data Sources

Sometimes it is necessary to use external data sources to provide parameters for the scraping process. For example, you have a database with a bunch of ASINs and you need to scrape all product information for each one of them. As far as Visual Web Ripper is concerned, an input data source can be used to provide a list of input values to a data extraction project. A data extraction project will be run once for each row of input values.

An input data source is normally used in one of these scenarios:

    To provide a list of input values for a web form
    To provide a list of start URLs
    To provide input values for Fixed Value elements
    To provide input values for scripts

Visual Web Ripper supports the following input data sources:

    SQL Server Database
    MySQL Database
    OleDB Database
    CSV File
    Script (A script can be used to provide data from almost any data source)

To see it in action you can download a sample project that uses an input CSV file with Amazon ASIN codes to generate Amazon start URLs and extract some product data. Place both the project file and the input CSV file in the default Visual Web Ripper project folder (My Documents\Visual Web Ripper\Projects).

For further information please look at the manual topic, explaining how to use an input data source to generate start URLs.


Source: http://extract-web-data.com/visual-web-ripper-using-external-input-data-sources/

Scraping Amazon.com with Screen Scraper

Let’s look how to use Screen Scraper for scraping Amazon products having a list of asins in external database.

Screen Scraper is designed to be interoperable with all sorts of databases and web-languages. There is even a data-manager that allows one to make a connection to a database (MySQL, Amazon RDS, MS SQL, MariaDB, PostgreSQL, etc), and then the scripting in screen-scraper is agnostic to the type of database.

Let’s go through a sample scrape project you can see it at work. I don’t know how well you know Screen Scraper, but I assume you have it installed, and a MySQL database you can use. You need to:

    Make sure screen-scraper is not running as workbench or server
    Put the Amazon (Scraping Session).sss file in the “screen-scraper enterprise edition/import” directory.
    Put the mysql-connector-java-5.1.22-bin.jar file in the “screen-scraper enterprise edition/lib/ext” directory.
    Create a MySQL database for the scrape to use, and import the amazon.sql file.
    Put the amazon.db.config file in the “screen-scraper enterprise edition/input” directory and edit it to contain proper settings to connect to your database.
    Start the screen scraper workbench

Since this is a very simple scrape, you just want to run it in the workbench (most of the time you want to run scrapes in server mode). Start the workbench, and you will see the Amazon scrape in there, and you can just click the “play” button.

Note that a breakpoint comes up for each item. It would be easy to save the scraped details to a database table or file if you want. Also see in the database the “id_status” changes as each item is scraped.

When the scrape is run, it looks in the database for products marked “not scraped”, so when you want to re-run the scrapes, you need to:

UPDATE asin
SET `id_status` = 0

Have a nice scraping! ))

P.S. We thank Jason Bellows from Ekiwi, LLC for such a great tutorial.


Source: http://extract-web-data.com/scraping-amazon-com-with-screen-scraper/

Using External Input Data in Off-the-shelf Web Scrapers

There is a question I’ve wanted to shed some light upon for a long time already: “What if I need to scrape several URL’s based on data in some external database?“.

For example, recently one of our visitors asked a very good question (thanks, Ed):

    “I have a large list of amazon.com asin. I would like to scrape 10 or so fields for each asin. Is there any web scraping software available that can read each asin from a database and form the destination url to be scraped like http://www.amazon.com/gp/product/{asin} and scrape the data?”

This question impelled me to investigate this matter. I contacted several web scraper developers, and they kindly provided me with detailed answers that allowed me to bring the following summary to your attention:
Visual Web Ripper

An input data source can be used to provide a list of input values to a data extraction project. A data extraction project will be run once for each row of input values. You can find the additional information here.
Web Content Extractor

You can use the -at”filename” command line option to add new URLs from TXT or CSV file:

    WCExtractor.exe projectfile -at”filename” -s

projectfile: the file name of the project (*.wcepr) to open.
filename – the file name of the CSV or TXT file that contains URLs separated by newlines.
-s – starts the extraction process

You can find some options and examples here.
Mozenda

Since Mozenda is cloud-based, the external data needs to be loaded up into the user’s Mozenda account. That data can then be easily used as part of the data extracting process. You can construct URLs, search for strings that match your inputs, or carry through several data fields from an input collection and add data to it as part of your output. The easiest way to get input data from an external source is to use the API to populate data into a Mozenda collection (in the user’s account). You can also input data in the Mozenda web console by importing a .csv file or importing one through our agent building tool.

Once the data is loaded into the cloud, you simply initiate building a Mozenda web agent and refer to that Data list. By using the Load page action and the variable from the inputs, you can construct a URL like http://www.amazon.com/gp/product/%asin%.
Helium Scraper

Here is a video showing how to do this with Helium Scraper:


The video shows how to use the input data as URLs and as search terms. There are many other ways you could use this data, way too many to fit in a video. Also, if you know SQL, you could run a query to get the data directly from an external MS Access database like
SELECT * FROM [MyTable] IN "C:\MyDatabase.mdb"

Note that the database needs to be a “.mdb” file.
WebSundew Data Extractor
Basically this allows using input data from external data sources. This may be CSV, Excel file or a Database (MySQL, MSSQL, etc). Here you can see how to do this in the case of an external file, but you can do it with a database in a similar way (you just need to write an SQL script that returns the necessary data).
In addition to passing URLs from the external sources you can pass other input parameters as well (input fields, for example).
Screen Scraper

Screen Scraper is really designed to be interoperable with all sorts of databases. We have composed a separate article where you can find a tutorial and a sample project about scraping Amazon products based on a list of their ASINs.


Source: http://extract-web-data.com/using-external-input-data-in-off-the-shelf-web-scrapers/

Selenium IDE and Web Scraping

Selenium is a browser automation framework that includes IDE, Remote Control server and bindings of various flavors including Java, .Net, Ruby, Python and other. In this post we touch on the basic structure of the framework and its application to  Web Scraping.
What is Selenium IDE


Selenium IDE is an integrated development environment for Selenium scripts. It is implemented as a Firefox plugin, and it allows recording browsers’ interactions in order to edit them. This works well for software tests, composing and debugging. The Selenium Remote Control is a server specific for a particular environment; it causes custom scripts to be implemented for controlled browsers. Selenium deploys on Windows, Linux, and iOS. How various Selenium components are supported with major browsers read here.
What does Selenium do and Web Scraping

Basically Selenium automates browsers. This ability is no doubt to be applied to web scraping. Since browsers (and Selenium) support JavaScript, jQuery and other methods working with dynamic content why not use this mix for benefit in web scraping, rather than to try to catch Ajax events with plain code? The second reason for this kind of scrape automation is browser-fasion data access (though today this is emulated with most libraries).

Yes, Selenium works to automate browsers, but how to control Selenium from a custom script to automate a browser for web scraping? There are Selenium PHP and other language libraries (bindings) providing for scripts to call and use Selenium. It is possible to write Selenium clients (using the libraries) in almost any language we prefer, for example Perl, Python, Java, PHP etc. Those libraries (API), along with a server, the Java written server that invokes browsers for actions, constitute the Selenum RC (Remote Control). Remote Control automatically loads the Selenium Core into the browser to control it. For more details in Selenium components refer to here.


A tough scrape task for programmer

“…cURL is good, but it is very basic.  I need to handle everything manually; I am creating HTTP requests by hand.
This gets difficult – I need to do a lot of work to make sure that the requests that I send are exactly the same as the requests that a browser would
send, both for my sake and for the website’s sake. (For my sake
because I want to get the right data, and for the website’s sake
because I don’t want to cause error messages or other problems on their site because I sent a bad request that messed with their web application).  And if there is any important javascript, I need to imitate it with PHP.
It would be a great benefit to me to be able to control a browser like Firefox with my code. It would solve all my problems regarding the emulation of a real browser…
it seems that Selenium will allow me to do this…” -Ryan S

Yes, that’s what we will consider below.
Scrape with Selenium

In order to create scripts that interact with the Selenium Server (Selenium RC, Selenium Remote Webdriver) or create local Selenium WebDriver script, there is the need to make use of language-specific client drivers (also called Formatters, they are included in the selenium-ide-1.10.0.xpi package). The Selenium servers, drivers and bindings are available at Selenium download page.
The basic recipe for scrape with Selenium:

    Use Chrome or Firefox browsers
    Get Firebug or Chrome Dev Tools (Cntl+Shift+I) in action.
    Install requirements (Remote control or WebDriver, libraries and other)
    Selenium IDE : Record a ‘test’ run thru a site, adding some assertions.
    Export as a Python (other language) script.
    Edit it (loops, data extraction, db input/output)
    Run script for the Remote Control

The short intro Slides for the scraping of tough websites with Python & Selenium are here (as Google Docs slides) and here (Slide Share).
Selenium components for Firefox installation guide

For how to install the Selenium IDE to Firefox see  here starting at slide 21. The Selenium Core and Remote Control installation instructions are there too.
Extracting for dynamic content using jQuery/JavaScript with Selenium

One programmer is doing a similar thing …

1. launch a selenium RC (remote control) server
2. load a page
3. inject the jQuery script
4. select the interested contents using jQuery/JavaScript
5. send back to the PHP client using JSON.

He particularly finds it quite easy and convenient to use jQuery for
screen scraping, rather than using PHP/XPath.
Conclusion

The Selenium IDE is the popular tool for browser automation, mostly for its software testing application, yet also in that Web Scraping techniques for tough dynamic websites may be implemented with IDE along with the Selenium Remote Control server. These are the basic steps for it:

    Record the ‘test‘ browser behavior in IDE and export it as the custom programming language script
    Formatted language script runs on the Remote Control server that forces browser to send HTTP requests and then script catches the Ajax powered responses to extract content.

Selenium based Web Scraping is an easy task for small scale projects, but it consumes a lot of memory resources, since for each request it will launch a new browser instance.



Source: http://extract-web-data.com/selenium-ide-and-web-scraping/

The Benefits of Data Outsourcing

Data is the foundation of all companies and provides a source for multiplying your company with tremendous leaps and bounds. The benefits of data entry outsourcing are numerous with expansion of methodologies, which provide your business with many other numerous benefits. Data entry is a generalized term, which entails virtual services like data mining, data conversion, image processing, web data entry, data extraction and many others. All of these tasks are very much a stronghold in getting the processes of any company streamlined without wasting time and resources.

If you think about the benefits of data-entry outsourcing, it is necessary for any company to add the need of data entry along with other important resources, which go with this task. It is also important to know the format, which the final version of data is to be utilized. You want to go for data that is available for usage in a cross platform environment.

There are many benefits of outsourcing. In today's society, data-entry services offer peace of mine as well as a sigh of relief for business owners. Here are some benefits which data-entry outsourcing companies can offer your company:

o Your complete data management needs being taken care of. When you outsource your data-entry needs to an outside company, you are going to benefit with having managed and synchronized data. This will ensure that your company will save time. The best thing about outsourcing companies is that some of the managed data can be utilized for repository purposes.

o Time is very critical when dealing with competition. You want to get data in and out of your business in order to reap the maximum possible benefits in the least amount of time. Utilizing an outsourcing company minimizes your time spent while improving the efficiency of your business processes.

o Your sole purpose for utilizing data-entry outsourcing companies should be to receive quality as well as the most quantity for your dollar. Quality cannot be compromised. Quantity also needs to be delivered fast and on time. There is no leeway given when it comes to data entry work. Receiving data-entry work on time with fast turn around allows your business to benefit with the business overhead.

o Outsourcing companies are affordable and what does this mean for your business? This will reduce your business costs while maximizing your profits.

With these benefits mentioned, data entry outsourcing offers a lot of potential for expansion for your company. Learn More About Data Entry Service.



Source: http://ezinearticles.com/?The-Benefits-of-Data-Outsourcing&id=3331295

Various Data Mining Techniques

Also called Knowledge Discover in Databases (KDD), data mining is the process of automatically sifting through large volumes of data for patterns, using tools such as clustering, classification, association rule mining, and many more. There are several major data mining techniques developed and known today, and this article will briefly tackle them, along with tools for increased efficiency, including phone look up services.

Classification is a classic data mining technique. Based on machine learning, it is used to classify each item on a data set into one of predefined set of groups or classes. This method uses mathematical techniques, like linear programming, decision trees, neural network, and statistics. For instance, you can apply this technique in an application that predicts which current employees will most probably leave in the future, based on the past records of those who have resigned or left the company.

Association is one of the most used techniques, and it is where a pattern is discovered basing on a relationship of a specific item on other items within the same transaction. Market basket analysis, for example, uses association to figure out what products or services are purchased together by clients. Businesses use the data produced to devise their marketing campaign.

Sequential patterns, too, aim to discover similar patterns in data transaction over a given business phase or period. These findings are used for business analysis to see relationships among data.

Clustering makes useful cluster of objects that maintain similar characteristics using an automatic method. While classification assigns objects into predefined classes, clustering defines the classes and puts objects in them. Predication, on the other hand, is a technique that digs into the relationship between independent variables and between dependent and independent variables. It can be used to predict profits in the future - a fitted regression curve used for profit prediction can be drawn from historical sale and profit data.

Of course, it is highly important to have high-quality data in all these data mining techniques. A multi-database web service, for instance, can be incorporated to provide the most accurate telephone number lookup. It delivers real-time access to a range of public, private, and proprietary telephone data. This type of phone look up service is fast-becoming a defacto standard for cleaning data and it communicates directly with telco data sources as well.

Phone number look up web services - just like lead, name, and address validation services - help make sure that information is always fresh, up-to-date, and in the best shape for data mining techniques to be applied.

Equip your business with better leads and get better conversion rates by using phone look up and similar real-time web services.




Source: http://ezinearticles.com/?Various-Data-Mining-Techniques&id=6985662

Unraveling the Data Mining Mystery - The Key to Dramatically Higher Profits

Data mining is the art of extracting nuggets of gold from a set of seemingly meaningless and random data. For the web, this data can be in the form of your server hit log, a database of visitors to your website or customers that have actually purchased from your web site at one time or another.

Today, we will look at how examining customer purchases can give you big clues to revising/improving your product selection, offering style and packaging of products for much greater profits from both your existing customers and an increased visitor to customer ratio.

To get a feel for this, lets take a look at John, a seller of vitamins and nutritional products on the internet. He has been online for two years and has made a fairly good living at selling vitamins and such online but knows he can do better but isn't sure how.

John was smart enough to keep all customer sales data in a database which was a good idea because it is now available for analysis. The first step is for John to run several reports from his database.

In this instance, these reports include: repeat customers, repeat customer frequency, most popular items, least popular items, item groups, item popularity by season, item popularity by geographic region and repeat orders for the same products. Lets take a brief look at each report and how it could guide John to greater profits.

    Repeat Customers - If I know who my repeat customers are, I can make special offers to them via email or offer them incentive coupons (if automated) surprise discounts at the checkout stand for being such a good customer.
    Repeat Customer Frequency - By knowing how often your customer buys from you, you can start tailoring automatic ship programs for that customer where every so many weeks, you will automatically ship the products the customer needs without the hassle of reordering. It shows the customer that you really value his time and appreciate his business.
    Repeat Orders - By knowing what a customer repeatedly buys and by knowing about your other products, you can make suggestions for additional complimentaty products for the customer to add to the order. You could even throw in free samples for the customer to try. And of course, you should try to get the customer on an auto-ship program.
    Most Popular Items - By knowing what items are purchased the most, you will know what items to highlight in your web site and what items would best be used as a loss-leader in a sale or packaged with other less popular items. If a popular product costs $20 and it is bundled with another $20 product and sold for $35, people will buy the bundle for the savings provided they perceive a need of some sort for the other product.
    Least Popular Items - This fact is useful for inventory control and for bundling (described above.) It is also useful for possible special sales to liquidate unpopular merchandise.
    Item Groups - Understanding item groups is very important in a retail environment. By understanding how customer's typically buy groups of products, you can redesign your display and packaging of items for sale to take advantage of this trend. For instance, if lots of people buy both Vitamin A and Vitamin C, it might make sense to bundle the two together at a small discount to move more product or at least put a hint on their respective web pages that they go great together.
    Item Popularity by season - Some items sell better in certain seasons than others. For instance, Vitamin C may sell better in winter than summer. By knowing the seasonability of the products, you will gain insight into what should be featured on your website and when.
    Item Popularity by Geographic Region - If you can find regional buying patterns in your customer base, you have a great opportunity for personalized, targeted mailings of specific products and product groups to each geographic region. Any time you can be more specific in your offering, your close percentage increases.

As you can see, each of these elements gives very valuable information that can help shape the future of this business and how it conducts itself on the web. It will dictate what new tools are needed, how data should be presented, whether or not a personal experience is justified (i.e. one that remembers you and presents itself based on your past interactions), how and when special sales should be run, what are good loss leaders, etc.

Although it can be quite a bit of work, data mining is a truly powerful way to dramatically increase your profit without incurring the cost of capturing new customers. The cost of being more responsive to an existing customer, making that customer feel welcome and selling that customer more product more often is far less costly than the cost of constantly getting new customers in a haphazard fashion.

Even applying the basic principles shared in this article, you will see a dramatic increase in your profits this coming year. And if you don't have good records, perhaps this is the time to start a system to track all this information. After all, you really don't want to be throwing all that extra money away, do you?




Source: http://ezinearticles.com/?Unraveling-the-Data-Mining-Mystery---The-Key-to-Dramatically-Higher-Profits&id=26665

Data Mining For Professional Service Firms - The Marketing Mother Lode May Already Be in Your Files

No one needs to tell you about the value of information in today's world--particularly the value of information that could help grow your practice. But has it occurred to you that you probably have more information in your head and your existing files that you realize? Tap into this gold mine of data to develop a powerful and effective marketing plan that will pull clients in the door and push your profitability up.

The way to do this is with data mining, which is the process of using your existing client data and demographics to highlight trends, make predictions and plan strategies.

In other words, do what other kinds of businesses have been doing for years: Analyze your clients by industry and size of business, the type and volume of services used, the amount billed, how quickly they pay and how profitable their business is to you. With this information, you'll be able to spot trends and put together a powerful marketing plan.

To data mine effectively, your marketing department needs access to client demographics and financial information. Your accounting department needs to provide numbers on the services billed, discounts given, the amounts actually collected, and receivables aging statistics. You may identify a specific service being utilized to a greater than average degree by a particular industry group, revealing a market segment worth pursuing. Or you may find an industry group that represents a significant portion of your billed revenue, but the business is only marginally profitable because of write-offs and discounts. In this case, you may want to shift your marketing focus.

You should also look at client revenues and profitability by the age of the clients. If your percentage of new clients is high, it could mean you're not retaining a sufficient number of existing clients. If you see too few new clients, you may be in for problems when natural client attrition is not balanced by new client acquisition.

The first step in effective data mining is to get everyone in the firm using the same information system. This allows everyone in the office who needs the names and addresses of the firm's clients and contacts to have access to that data. Require everyone to record notes on conversations and meetings in the system. Of course, the system should also accommodate information that users don't want to share, such as client's private numbers or the user's personal contacts. This way, everyone can utilize the system for everything, which makes them more likely to use it completely.

Your information system can be either contact information or customer relationship management software (a variety of packages are on the market) or you can have a system custom designed. When considering software to facilitate data mining, look at three key factors:

1. Ease of use. If the program isn't easy to use, it won't get used, and will end up being just a waste of time and money.

2. Accessibility. The system must allow for data to be accessible from anywhere, including laptops, hand-held devices, from the internet or cell phones. The data should also be accessible from a variety of applications so it can be used by everyone in the office all the time, regardless of where they are.

3. Sharability. Everyone needs to be able to access the information, but you also need privacy and editing rights so you can assign or restrict what various users can see and input.

Don't overlook the issue of information security. Beyond allowing people the ability to code certain entries as private, keep in mind that anyone with access to the system as the ability to either steal information or sabotage your operation. Talk to your software vendor about various security measures but don't let too much security make the system unusable. Protect yourself contractually with noncompete and nondisclosure agreements and be sure to back up your data regularly.

Finally, expect some staffers to resist when you ask them to change from the system they've been using. You may have to sell them on the benefits outweighing the pain of making a change and learning the new system--which means you need to be totally sold on it yourself. The managing partner, or the leader of the firm, needs to be driving this initiative for it to succeed. When it does succeed, you'll be able to focus your marketing dollars and efforts in the most profitable areas with the least expense, with a tremendous positive impact on the bottom line.

Jacquelyn Lynn is a business writer and ghostwriter based in Orlando, Florida. She is the author or ghostwriter of more than 25 books, including Entrepreneur's Almanac; Online Shopper's Survival Guide; Make Big Profits on eBay (with Charlene Davis); In Search of the Five-Cent Nickel (with Don Abbott); and 11 titles in Entrepreneur Media's StartUp Guide series.



Source: http://ezinearticles.com/?Data-Mining-For-Professional-Service-Firms---The-Marketing-Mother-Lode-May-Already-Be-in-Your-Files&id=4607430

Unleash the Hidden Potential of Your Business Data With Data Mining and Extraction Services

Every business, small or large, is continuously amassing data about customers, employees and nearly every process in their business cycle. Although all management staff utilize data collected from their business as a basis for decision making in areas such as marketing, forecasting, planning and trouble-shooting, very often they are just barely scratching the surface. Manual data analysis is time-consuming and error-prone, and its limited functions result in the overlooking of valuable information that improve bottom-lines. Often, the sheer quantity of data prevents accurate and useful analysis by those without the necessary technology and experience. It is an unfortunate reality that much of this data goes to waste and companies often never realize that a valuable resource is being left untapped.

Automated data mining services allow your company to tap into the latent potential of large volumes of raw data and convert it into information that can be used in decision-making. While the use of the latest software makes data mining and data extraction fast and affordable, experienced professional data analysts are a key part of the data mining services offered by our company. Making the most of your data involves more than automatically generated reports from statistical software. It takes analysis and interpretation skills that can only be performed by experienced data analysis experts to ensure that your business databases are translated into information that you can easily comprehend and use in almost every aspect of your business.

Who Can Benefit From Data Mining Services?

If you are wondering what types of companies can benefit from data extraction services, the answer is virtually every type of business. This includes organizations dealing in customer service, sales and marketing, financial products, research and insurance.

How is Raw Data Converted to Useful Information?

There are several steps in data mining and extraction, but the most important thing for you as a business owner is to be assured that, throughout the process, the confidentiality of your data is our primary concern. Upon receiving your data, it is converted into the necessary format so that it can be entered into a data warehouse system. Next, it is compiled into a database, which is then sifted through by data mining experts to identify relevant data. Our trained and experienced staff then scan and analyze your data using a variety of methods to identify association or relationships between variables; clusters and classes, to identify correlations and groups within your data; and patterns, which allow trends to be identified and predictions to be made. Finally, the results are compiled in the form of written reports, visual data and spreadsheets, according to the needs of your business.

Our team of data mining, extraction and analyses experts have already helped a great number of businesses to tap into the potential of their raw data, with our speedy, cost-efficient and confidential services. Contact us today for more information on how our data mining and extraction services can help your business.





Source: http://ezinearticles.com/?Unleash-the-Hidden-Potential-of-Your-Business-Data-With-Data-Mining-and-Extraction-Services&id=4642076

Should Corporate Think Tanks Scan IT Logs, and Data Mine for Innovative Ideas?

Most people in the corporate environment would have a problem with their bosses snooping their e-mails. Nevertheless, we know this happens every day because the employers want to make sure their employees are not screwing off and wasting company time. Every CFO knows that productivity in the workplace, or office environment is paramount to profits. Now then, I have another question, one that you have not considered yet regarding this issue.

My question is this; what if your employer was snooping your e-mails and looking for ideas which you had when corresponding with various vendors, customers, or other employees? That is to say what if your employer had an algorithm, which searched for keywords in e-mail correspondence that could give them insight into innovative ways to modify their products or services? Would you as employee be upset about something like that?

In other words, they are not looking to get you in trouble, rather they are looking for ideas and innovations which will help the company do better in the marketplace, become more efficient, and help the company achieve its quarterly objectives, while increasing shareholders equity.

There was an interesting article posted in MIT's Technology Review titled "Extracting Business Ideas from IT Logs Software finds hidden business insights in Web and phone logs, e-mail, and network traffic," posted on Friday, February 11, 2011 by Tom Simonite.

Indeed, I find this very interesting because as the coordinator for a think tank which operates on the Internet, it always occurred to me that perhaps we should have an algorithm that searches through all the e-mails to find the smartest humans amongst us, and perhaps hire them to help with legislative, judicial, military, and executive decisions in the government.

What if businesses, corporations, universities, nonprofits, and government agencies started doing this with all their employees? And what if Google came up with a similar system to find innovative ideas, would anyone really want their data anonymized in that case? Chances are they wouldn't, chances are they would like to participate in such a program, and perhaps in the future get paid for their ideas, or get a small stipend, royalty, or kudos for their innovative ideas and concepts.

It's not that I wish to suggest that we should by spying on the American people, but since we already are (NSA) and I think everyone knows that, maybe we should start looking for the good guys, as well as the bad guys? Indeed, I hope you will take this thought on a philosophical basis, and please consider what I've said here today.

Lance Winslow is the Founder of the Online Think Tank, a diverse group of achievers, experts, innovators, entrepreneurs, thinkers, futurists, academics, dreamers, leaders, and general all around brilliant minds. Lance Winslow hopes you've enjoyed today's discussion and topic. http://www.WorldThinkTank.net - Have an important subject to discuss, contact Lance Winslow.




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Data Mining Is Useful for Business Application and Market Research Services

One day of data mining is an important tool in a market for modern business and market research to transform data into an information system advantage. Most companies in India that offers a complete solution and services for these services. The extraction or to provide companies with important information for analysis and research.

These services are primarily today by companies because the firm body search of all trade associations, retail, financial or market, the institute and the government needs a large amount of information for their development of market research. This service allows you to receive all types of information when needed. With this method, you simply remove your name and information filter.

This service is of great importance, because their applications to help businesses understand that it can perform actions and consumer buying trends and industry analysis, etc. There are business applications use these services:
1) Research Services
2) consumption behavior
3) E-commerce
4) Direct marketing
5) financial services and
6) customer relationship management, etc.

Benefits of Data mining services in Business

• Understand the customer need for better decision
• Generate more business
• Target the Relevant Market.
• Risk free outsourcing experience
• Provide data access to business analysts
• Help to minimize risk and improve ROI.
• Improve profitability by detect unusual pattern in sales, claims, transactions
• Major decrease in Direct Marketing expenses

Understanding the customer's need for a better fit to generate more business target market.To provide risk-free outsourcing experience data access for business analysts to minimize risk and improve return on investment.

The use of these services in the area to help ensure that the data more relevant to business applications. The different types of text mining such as mining, web mining, relational databases, data mining, graphics, audio and video industry, which all used in enterprise applications.




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Data Mining: Its Description and Uses

Data mining also known as the process of analyzing the KDD which stands for Knowledge Discovery in Databases is a part of statistics and computer science. It is a process which aims to find out many various patterns in enormous sets of relational data.

It uses ways at the fields of machine learning, database systems, artificial intelligence, and statistics. It permits users to examine data from many various perspectives, sort it, and summarize the identified relationships.

In general, the objective of data mining process is to obtain info out of a data set and convert it into a comprehensible outline. Also, it includes the following: data processing, data management and database aspects, visualization, complexity considerations, online updating, inference and model considerations, and interestingness metrics.

On the other hand, the actual data mining assignment is the semi-automatic or automatic exploration of huge quantities of information to extract patterns that are interesting and previously unknown. Such patterns can be the unusual records or the anomaly detection, data records groups or the cluster analysis, and the dependencies or the association rule mining. Usually, this involves utilizing database methods like spatial indexes. Such patters could be perceived as a type of summary of input data, and could be used in further examination or, for example, in predictive analysis and machine learning.

Today, data mining is utilized by different consumer-focused companies like those in the financial, retails, marketing, and communications fields. It permits such companies to find out relationships among the internal aspects like staff skills, price, product positioning, and external aspects like customer information, competition, and economic indicators. Additionally, it allows them to define the effect on corporate profits, sales, and customer satisfaction; and dig into the summary information to be able to see transactional data in detail.

With data mining process, a retailer can make use of point-of-scale customer purchases records to send promotions based on the purchase history of a client. The retailer can improve products and campaigns or promotions that can be appealing to a definite customer group by using mining data from comment cards.

Generally, any of the following relationships are obtained.

1. Associations: Data could be mined to recognize associations.
2. Clusters: Data are sorted based on a rational relationships or consumer preferences.
3. Sequential Patters: Data is mined to expect patterns and trends in behavior.
4. Classes: Data that are stored are utilized to trace data in predetermined segments.




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Data Mining, Not Just a Method But a Technique

Web data mining is segregating probable clients out of huge information available on the Internet by performing various searches. It could be well organized and structured, or raw, depending on the use of the data. Web data mining could be done using a simple database program or investing money in a costly program.

Start collecting basic contact information of probable clients, such as: names, addresses, landline and cell phone numbers, email addresses and education or occupation if required.

CART and CHAID data mining

While collecting data you will find that tree-shaped structures that represent decisions. These derived decisions give rules for the classification of data collected. Precise decision tree methods include Classification and Regression Trees also know as CART data mining and Chi Square Automatic Interaction Detection also known as CHAID data mining. CART and CHAID data mining are decision tree techniques used for classification of data collected. They provide a set of rules that could be applied to unclassified data collected in prediction. CART segments a dataset creating two-way splits whereas CHAID segments using chi square tests creating multi-way splits. CART requires less data preparation compared to CHAID.

Understanding customer's actions

Keep a track of customer's actions like: what does he buy, when does he buy, why does he buy, what is the use of his buying, etc. Knowing such simple things about your customer will help you to understand needs of your customer better and thus process of data mining services will be easier and quality data would be mined. This will increase your personal relations with your customer which would finally result in a better professional relationship.

Following demography

Mine the data as per demography, dependent on geography as well as socio economic background of business location. You can use government statistics as the source of your data collection. Keeping it in mind you can go ahead with the understanding of the community existing and thus the data required.

Use your informal conversation in serving your clients better

Use minute details of your conversation and understanding with your customers to serve them. If essential, conduct surveys, send a professional gift or use some other object that helps you understand better in fulfilling customer needs. This will increase the bonding between you and your customer and you will be able to serve your customer better in providing data mining services.

Insert the collect information in a desktop database. More the information is collected you will find that you can prepare specific templates in feeding information. Using a desktop database, it is easier to make changes later on as and when required.

Maintaining privacy

While performing, it is essential to ensure that you or your team members are not violating privacy laws in gathering or providing the data information. Once trust is lost, you may also loose the customer, because trust is the base of any relationship, let it be a business relation.




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Text Data Mining Can Be Profitable

There are billions of search terms performed on the internet every year,and the companies which make use of this vast amount of information are the ones who will be able to market effectively in the future. It is here that text data mining comes into its own, a technique which enables researchers to find patterns within groups of text which will enable them to make predictions as to how customers or other groups of people will act in the future. This article will take a look at text data mining and how we can help various groups of people to find the best things in the data analysis.

It is always a good idea to do some study of the text mining techniques before going on to text mining implementation, and this can be said to be especially true of the insurance industry where not only text mining but also generic data mining using in statistics can be a great help in determining profitability and also showing actuaries how to make future calculations.

Consultancy is an important part of text data mining, and the text mining consultant can bring a huge amount of knowledge to a company whatever the service or services that are providing, particularly if he has an extensive knowledge of text data mining technology and can help to build a system around it.

Of course it is not only commercial applications that can use text mining, because it also has used in security, in that it can help to track criminal intent on the Internet. There are also applications in the biomedical world, in order to help find clusters of data in the right way. But it is in the online world and in the field of marketing that text mining is being used extensively, particularly in customer relationship management [CRM] techniques, where the tools are among some of the most advanced.

Knowing how text mining algorithms work is essential for any consultant who works in this field, because it is an important tool in the marketing technique possibilities. By understanding how text data mining can help an organization a consultant or marketer can make great strides in profitability and this is something that most organizations would be glad for.




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Customer Relationship Management (CRM) Using Data Mining Services

In today's globalized marketplace Customer relationship management (CRM) is deemed as crucial business activity to compete efficiently and outdone the competition. CRM strategies heavily depend on how effectively you can use the customer information in meeting their needs and expectations which in turn leads to more profit.

Some basic questions include - what are their specific needs, how satisfied they are with your product or services, is there a scope of improvement in existing product/service and so on. For better CRM strategy you need a predictive data mining models fueled by right data and analysis. Let me give you a basic idea on how you can use Data mining for your CRM objective.

Basic process of CRM data mining includes:
1. Define business goal
2. Construct marketing database
3. Analyze data
4. Visualize a model
5. Explore model
6. Set up model & start monitoring

Let me explain last three steps in detail.

Visualize a Model:
Building a predictive data model is an iterative process. You may require 2-3 models in order to discover the one that best suit your business problem. In searching a right data model you may need to go back, do some changes or even change your problem statement.

In building a model you start with customer data for which the result is already known. For example, you may have to do a test mailing to discover how many people will reply to your mail. You then divide this information into two groups. On the first group, you predict your desired model and apply this on remaining data. Once you finish the estimation and testing process you are left with a model that best suits your business idea.

Explore Model:
Accuracy is the key in evaluating your outcomes. For example, predictive models acquired through data mining may be clubbed with the insights of domain experts and can be used in a large project that can serve to various kinds of people. The way data mining is used in an application is decided by the nature of customer interaction. In most cases either customer contacts you or you contact them.

Set up Model & Start Monitoring:
To analyze customer interactions you need to consider factors like who originated the contact, whether it was direct or social media campaign, brand awareness of your company, etc. Then you select a sample of users to be contacted by applying the model to your existing customer database. In case of advertising campaigns you match the profiles of potential users discovered by your model to the profile of the users your campaign will reach.

In either case, if the input data involves income, age and gender demography, but the model demands gender-to-income or age-to-income ratio then you need to transform your existing database accordingly.



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Data Mining Tools - Understanding Data Mining

Data mining basically means pulling out important information from huge volume of data. Data mining tools are used for the purposes of examining the data from various viewpoints and summarizing it into a useful database library. However, lately these tools have become computer based applications in order to handle the growing amount of data. They are also sometimes referred to as knowledge discovery tools.

As a concept, data mining has always existed since the past and manual processes were used as data mining tools. Later with the advent of fast processing computers, analytical software tools, and increased storage capacities automated tools were developed, which drastically improved the accuracy of analysis, data mining speed, and also brought down the costs of operation. These methods of data mining are essentially employed to facilitate following major elements:

    Pull out, convert, and load data to a data warehouse system
    Collect and handle the data in a database system
    Allow the concerned personnel to retrieve the data
    Data analysis
    Data presentation in a format that can be easily interpreted for further decision making

We use these methods of mining data to explore the correlations, associations, and trends in the stored data that are generally based on the following types of relationships:

    Associations - simple relationships between the data
    Clusters - logical correlations are used to categorise the collected data
    Classes - certain predefined groups are drawn out and then data within the stored information is searched based on these groups
    Sequential patterns - this helps to predict a particular behavior based on the trends observed in the stored data

Industries which cater heavily to consumers in retail, financial, entertainment, sports, hospitality and so on rely on these data methods of obtaining fast answers to questions to improve their business. The tools help them to study to the buying patterns of their consumers and hence plan a strategy for the future to improve sales. For e.g. restaurant might want to study the eating habits of their consumers at various times during the day. The data would then help them in deciding on the menu at different times of the day. Data mining tools certainly help a great deal when drawing out business plans, advertising strategies, discount plans, and so on. Some important factors to consider when selecting a data mining tool include the platforms supported, algorithms on which they work (neural networks, decisions trees), input and output options for data, database structure and storage required, usability and ease of operation, automation processes, and reporting methods.


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What is Data Mining?

Data mining is the process in which there is analysis of data forming different angles and perspectives and summarizing the same data into the relevant information. This kind of information could be utilized to increase the revenue, cutting the costs or both.

Software is mainly used for analyzing data and also assists in accumulation of data for the different sources and categorize and summarize the given data into some useful form.

Though the data mining is new term, the software used for mining the data was previously used. With the constant upgradations of the software and the processing power, the market tools, data mining software has increased in its accuracy. Formerly, this data mining was widely used by the businessmen for the market research and the analysis. There were few companies that used the computers to examine through the column of the supermarket data.

The data mining is the technique of running the data through the sophisticated algorithms for discovering the meaningful correlations and patterns that would have otherwise remained hidden. It is very helpful, since it aids in understanding the techniques and methods of business and you can accordingly apply your own intelligence fitting in the current market trend. Even the future performances get enhanced by the predictive analysis.

Business Intelligence operations occur in the background. Users of the mining operation can just see the end result. The users are in apposition to get the results through the mails and can also go through the recommendation through web pages and emails.

The data mining process indicates the invention of trends and tactics. The moment you discover and understand the market trends, you have the knowledge of which article is sold more and which article is sold with the other one. This kind of tend has an enormous impact on business organization. In this manner, the business gets enhanced as the market gets analyzed in a perfect manner. Due to these correlations, the performance of business organization increases to a lot of extent.

Mining gives a chance or opportunity to enhance the future performance of the business organization. There is a common philosophical phrase that, 'he who does not learn from the history is destined to repeat the same'. Therefore, if these predictions are done with the help and assistance of the historical information (data), then you can get sufficient data for improvising the products of the business organization.

Mining enables the embedding of the recommendations in the applications. Simple summary statements and the proposals can be displayed within the operational applications. Data mining also needs powerful machines. The algorithms might be applied to a Java or a Dataset code for using the same. Data mining is very useful for knowing the trends and making future predictions based on the predictive analysis. It also helps in cost cutting and increase in the revenue of the business organization


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Should I Outsource My Data Entry? Selecting the Right Vendor

Should I outsource my data entry? How do I know if a vendor is any good? Questions every company or organization ask. Whether you are a small company wanting to create a mailing list of your clients, or a large multi-national company engaged in an ongoing loyalty card marketing campaign, data entry work is a universal service that almost every company, at some point, finds necessary.

First, you need to decide if outsourcing your data entry needs is right for you. Here are a few reasons why organizations choose to outsource.

Cost
Hands down, lowering internal cost is the primary reason why most decide to try and outsource their data entry work. Instead of paying employees to perform data entry jobs, they outsource the work to third party vendors.

High Quality Work
Let the experts do the work. Let's face it, if your employee is not engaged in regular data entry work the skill set just might not be there. Third party vendors generally can produce much higher quality work, simply because they are the experts. A reputable company will offer quality guarantees based on the type of work and how you choose to have the work keyed.

Turn Time (speed)
Getting you work back quickly is an important fact of business. Most third party vendors have a large staff of workers ready to work on your project, and can spread out the work thus greatly increasing the production rate.

Ok, so now we have decided that outsourcing is the way to go. What next? Ahhh... the all important task of selecting the right vendor for you.

A simple search on the web and you will find yourself swamped with ads offering data entry services (as well as those ads offering at home work opportunities), so how do you know who to pick. Well before you just throw darts at a list, there are few questions you might first ask yourself.

•Do I want my work to be completed in the US, or offshore?
•How do I want my data to look when it is returned to me?
•What information do I want collected?
•Do I want to physically send the originals?
•What is my budget?
•How soon do I need the work completed

These are just a few sample questions, designed to get the brain thinking and get you on the right track.

As with all things in life, asking questions is the best way to make an informed decision. Here are few essential questions, I recommend asking any data entry vendor you are considering.
• How big is your company? do you specialize in any particular type of data entry? And how many projects have you worked on?
•Has your company done or are currently working on projects similar to mine?
•Do you make client references available?
•What resources and software do you have available and use?
•Will my data be safe and kept confidential?
•Where is your work done? Do you offer domestic and offshore options?
Again, these are just a few questions to keep in mind. You will have questions specific to your project you will want to ask.



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Data Conversion Services - Transform Your Data Professionally

Data is least comprehensible when it is in a format unsupported by many of the usual data reading systems. This leaves us with a prudent choice - to convert data, which are in different formats to one or many of those commonly used formats. However, conversion shall get tricky and tedious if done by people who don't have any proficiency in transforming the formats. Data conversion services are being done by a team of experts who form a company and do this quite professionally. Resorting to such professionals would mean a lot to your business since they are the ones who are capable of producing desires output with the least possible proportion of error in the documented files that they submit at the end of the conversion process.

Many service providers especially from India have proven their capabilities of handling bulk projects quite regularly yet being able to deliver error-free documented forms of the desired output. To add, they have got the right mix of technological resources in the shape of few domestic systems in conjunction with a few resourceful application software with which they are able to deliver results every time. Plus, they also tend to put a line of validating systems in place so as to make sure there is not any undesirable change effected in the output once the conversion process is done. Once they manage to find a few mistakes or anomalies in the conversion system, they don't hesitate to overcome those by putting them under check and removing the bugs at necessary instances.

Only quite a few types of conversion are beholden as to be the primary ones having superior importance to several conversion mechanisms. In fact, the scenario is that the large scale and medium scale businesses demand only quite a few conversion mechanisms such as the PDF Conversion, XML Conversion, Book conversion, HTML Conversion to end with the OCR conversion. Through such a scattered set of primary data conversion practices, they lend their hand to assist in converting, extracting relevant amount of data from the sources, transcribing the rich set of essential information relevant to the current needs of the client and consolidating data so that on the whole the entire set of converted data is compatible to be read by the systems incorporated in the client's place.

No doubt, the data presented to them regardless of its format will be returned as a readily usable piece of information that can be customized to any form that we need it to see in. In most of the cases, they do not consume much of the time than what they should be given since they are dealing with several processes concurrently whose progress reflects on the output you receive from them. Moreover, they also shunt the possibility of these important data to be hacked by any third party by providing enough protection. Till niow, you have been reading about some benefits that you enjoy about the data conversion services, which do not charge much for working on your documents. Isn't it the biggest of all benefits?

Isn't it something important to catch hold of a reliable data conversion services provider? If you think so simply follow this link and you would get close to having a high-quality data conversion services transform raw data into usable piece of official information.



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Data Mining And Importance to Achieve Competitive Edge in Business

What is data mining? And why it is so much importance in business? These are simple yet complicated questions to be answered, below is brief information to help understanding data and web mining services.

Mining of data in general terms can be elaborated as retrieving useful information or knowledge for further process of analyzing from various perspectives and summarizing in valuable information to be used for increasing revenue, cut cost, to gather competitive information on business or product. And data abstraction finds a great importance in business world as it help business to harness the power of accurate information thus providing competitive edge in business. May business firms and companies have their own warehouse to help them collect, organize and mine information such as transactional data, purchase data etc.

But to have a mining services and warehouse at premises is not affordable and not very cost effective to solution for reliable information solutions. But as if taking out of information is the need for every business now days. Many companies are providing accurate and effective data and web data mining solutions at reasonable price.

Outsourcing information abstraction services are offered at affordable rates and it is available for wide range of data mine solutions:

• taking out business data
• service to gather data sets
• digging information of datasets
• Website data mining
• stock market information
• Statistical information
• Information classification
• Information regression
• Structured data analysis
• Online mining of data to gather product details
• to gather prices
• to gather product specifications
• to gather images

Outsource web mining solutions and data gathering solutions has been effective in terms of cost cutting, increasing productivity at affordable rates. Benefits of data mining services include:

• clear customer, service or product understanding
• less or minimal marketing cost
• exact information on sales, transactions
• detection of beneficial patterns
• minimizing risk and increased ROI
• new market detection
• Understanding clear business problems and goals

Accurate data mining solutions could prove to be an effective way to cut down cost by concentrating on right place.




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What is Data Mining? Why Data Mining is Important?

Searching, Collecting, Filtering and Analyzing of data define as data mining. The large amount of information can be retrieved from wide range of form such as different data relationships, patterns or any significant statistical co-relations. Today the advent of computers, large databases and the internet is make easier way to collect millions, billions and even trillions of pieces of data that can be systematically analyzed to help look for relationships and to seek solutions to difficult problems.

The government, private company, large organization and all businesses are looking for large volume of information collection for research and business development. These all collected data can be stored by them to future use. Such kind of information is most important whenever it is require. It will take very much time for searching and find require information from the internet or any other resources.

Here is an overview of data mining services inclusion:

* Market research, product research, survey and analysis
* Collection information about investors, funds and investments
* Forums, blogs and other resources for customer views/opinions
* Scanning large volumes of data
* Information extraction
* Pre-processing of data from the data warehouse
* Meta data extraction
* Web data online mining services
* data online mining research
* Online newspaper and news sources information research
* Excel sheet presentation of data collected from online sources
* Competitor analysis
* data mining books
* Information interpretation
* Updating collected data

After applying the process of data mining, you can easily information extract from filtered information and processing the refining the information. This data process is mainly divided into 3 sections; pre-processing, mining and validation. In short, data online mining is a process of converting data into authentic information.

The most important is that it takes much time to find important information from the data. If you want to grow your business rapidly, you must take quick and accurate decisions to grab timely available opportunities.

Outsourcing Web Research is one of the best data mining outsourcing organizations having more than 17 years of experience in the market research industry. To know more information about our company please contact us.



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Data Mining - Critical for Businesses to Tap the Unexplored Market

Knowledge discovery in databases (KDD) is an emerging field and is increasingly gaining importance in today's business. The knowledge discovery process, however, is vast, involving understanding of the business and its requirements, data selection, processing, mining and evaluation or interpretation; it does not have any pre-defined set of rules to go about solving a problem. Among the other stages, the data mining process holds high importance as the task involves identification of new patterns that have not been detected earlier from the dataset. This is relatively a broad concept involving web mining, text mining, online mining etc.

What Data Mining is and what it is not?

The data mining is the process of extracting information, which has been collected, analyzed and prepared, from the dataset and identifying new patterns from that information. At this juncture, it is also important to understand what it is not. The concept is often misunderstood for knowledge gathering, processing, analysis and interpretation/ inference derivation. While these processes are absolutely not data mining, they are very much necessary for its successful implementation.

The 'First-mover Advantage'

One of the major goals of the data mining process is to identify an unknown or rather unexplored segment that had always existed in the business or industry, but was overlooked. The process, when done meticulously using appropriate techniques, could even make way for niche segments providing companies the first-mover advantage. In any industry, the first-mover would bag the maximum benefits and exploit resources besides setting standards for other players to follow. The whole process is thus considered to be a worthy approach to identify unknown segments.

The online knowledge collection and research is the concept involving many complications and, therefore, outsourcing the data mining services often proves viable for large companies that cannot devote time for the task. Outsourcing the web mining services or text mining services would save an organization's productive time which would otherwise be spent in researching.

The data mining algorithms and challenges

Every data mining task follows certain algorithms using statistical methods, cluster analysis or decision tree techniques. However, there is no single universally accepted technique that can be adopted for all. Rather, the process completely depends on the nature of the business, industry and its requirements. Thus, appropriate methods have to be chosen depending upon the business operations.

The whole process is a subset of knowledge discovery process and as such involves different challenges. Analysis and preparation of dataset is very crucial as the well-researched material could assist in extracting only the relevant yet unidentified information useful for the business. Hence, the analysis of the gathered material and preparation of dataset, which also considers industrial standards during the process, would consume more time and labor. Investment is another major challenge in the process as it involves huge cost on deploying professionals with adequate domain knowledge plus knowledge on statistical and technological aspects.

The importance of maintaining a comprehensive database prompted the need for data mining which, in turn, paved way for niche concepts. Though the concept has been present for years now, companies faced with ever growing competition have realized its importance only in the recent years. Besides being relevant, the dataset from where the information is actually extracted also has to be sufficient enough so as to pull out and identify a new dimension. Yet, a standardized approach would result in better understanding and implementation of the newly identified patterns.


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Importance of Data Mining Services in Business

Data mining is used in re-establishment of hidden information of the data of the algorithms. It helps to extract the useful information starting from the data, which can be useful to make practical interpretations for the decision making.
It can be technically defined as automated extraction of hidden information of great databases for the predictive analysis. In other words, it is the retrieval of useful information from large masses of data, which is also presented in an analyzed form for specific decision-making. Although data mining is a relatively new term, the technology is not. It is thus also known as Knowledge discovery in databases since it grip searching for implied information in large databases.
It is primarily used today by companies with a strong customer focus - retail, financial, communication and marketing organizations. It is having lot of importance because of its huge applicability. It is being used increasingly in business applications for understanding and then predicting valuable data, like consumer buying actions and buying tendency, profiles of customers, industry analysis, etc. It is used in several applications like market research, consumer behavior, direct marketing, bioinformatics, genetics, text analysis, e-commerce, customer relationship management and financial services.

However, the use of some advanced technologies makes it a decision making tool as well. It is used in market research, industry research and for competitor analysis. It has applications in major industries like direct marketing, e-commerce, customer relationship management, scientific tests, genetics, financial services and utilities.

Data mining consists of major elements:

    Extract and load operation data onto the data store system.
    Store and manage the data in a multidimensional database system.
    Provide data access to business analysts and information technology professionals.
    Analyze the data by application software.
    Present the data in a useful format, such as a graph or table.

The use of data mining in business makes the data more related in application. There are several kinds of data mining: text mining, web mining, relational databases, graphic data mining, audio mining and video mining, which are all used in business intelligence applications. Data mining software is used to analyze consumer data and trends in banking as well as many other industries.




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